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@ARTICLE{Adini1997,
  author = {Y. Adini and Y. Moses and S. Ullman},
  title = {Face recognition: The problem of compensating for changes in illumination
	direction},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1997},
  volume = {19},
  pages = {721-732},
  number = {7}
}

@ARTICLE{Ahonen2006,
  author = {Timo Ahonen and Abdenour Hadid and Matti Pietikainen},
  title = {Face Description with Local Binary Patterns: Application to Face
	Recognition},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2006},
  volume = {28},
  pages = {2037-2041},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@CONFERENCE{Ahonen2004,
  author = {Ahonen, Timo and Hadid, Abdenour and Pietikainen, Matti},
  title = {Face Recognition with Local Binary Patterns},
  booktitle = {Proceedings of European Conference on Computer Vision},
  year = {2004},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@CONFERENCE{Aloni2004,
  author = {Dan Aloni},
  title = {Cooperative Linux},
  booktitle = {Proceedings of the Linux Symposium},
  year = {2004}
}

@INPROCEEDINGS{Alsabti1998,
  author = {K. Alsabti and S. Ranka and V. Singh},
  title = {An Efficient k-means Clustering Algorithm},
  booktitle = {Proceedings of International Parallel Processing Symposium},
  year = {1998}
}

@ARTICLE{Anderson2002,
  author = {David P. Anderson and Jeff Cobb and Eric Korpela and Matt Lebofsky
	and Dan Werthimer},
  title = {{SETI@home}: An Experiment in Public-Resource Computing},
  journal = {Communications of the ACM},
  year = {2002},
  volume = {45},
  pages = {56-61},
  number = {11},
  month = {November},
  abstract = {SETI@home uses computers in homes and offices around the world to
	analyze radio telescope signals. This approach, though it presents
	some difficulties, has provided unprecedented computing power and
	has led to a unique public involvement in science. We describe SETI@home's
	design and implementation, and discuss its relevance to future distributed
	systems.}
}

@ARTICLE{Anderson1935,
  author = {Edgar Anderson},
  title = {The irises of the Gaspe Peninsula},
  journal = {Bulletin of the American Iris Society},
  year = {1935},
  volume = {59},
  pages = {2-5}
}

@CONFERENCE{Asami2005,
  author = {Taichi Asami and Koji Iwano and Sadaoki Furui},
  title = {Stream-Weight Optimization by {LDA} and {A}daboost for Multi-Stream
	Speaker Verification},
  booktitle = {Proceedings of International Conference on Speech Communication and
	Technology (Interspeech 2005)},
  year = {2005},
  pages = {2185-2188},
  address = {Lisbon, Portugal}
}

@INPROCEEDINGS{Augusteijn1993,
  author = {M.F. Augusteijn and T.L. Skufca},
  title = {Identification of human faces through texture-based featurerecognition
	andneural network technology},
  booktitle = {IEEE International Conference on Neural Networks},
  year = {1993},
  pages = {392-398},
  month = {March}
}

@ARTICLE{Bach2002,
  author = {F.R. Bach and M.I. Jordan},
  title = {Kernel Independent Component Analysis},
  journal = {Journal of Machine Learning Research},
  year = {2002},
  volume = {3},
  pages = {1-48}
}

@CONFERENCE{Baek2002,
  author = {Kyungim Baek and Bruce A. Draper and J. Ross Beveridge and Kai She},
  title = {{PCA} vs. {ICA}: A comparison on the {FERET} data set},
  booktitle = {In Proceedings of Joint Conference on Information Sciences},
  year = {2002}
}

@MISC{Ballard1939,
  author = {Randall C. Ballard},
  title = {TELEVISION SYSTEM},
  howpublished = {Patent},
  month = {3},
  year = {1939},
  note = {Patent number: 2152234},
  owner = {Radio Corporation of America},
  url = {http://www.google.com/patents?id=H49TAAAAEBAJ&dq=patent:2152234}
}

@ARTICLE{Bartlett1998,
  author = {M.S. Bartlett and H.M. Lades and T.J. Sejnowski},
  title = {Independent Component Representations for Face Recognition},
  journal = {Proceedings of SPIE},
  year = {1998},
  volume = {3299},
  pages = {528-539}
}

@ARTICLE{Bartlett2002,
  author = {M.S. Bartlett and J.R. Movellan and T.J. Sejnowski},
  title = {Face recognition by Independent component analysis},
  journal = {IEEE Transactions on Neural Networks},
  year = {2002},
  volume = {13},
  pages = {1450-1464}
}

@ARTICLE{Belhumeur1997,
  author = {P.N. Belhumeur and J.P. Hespanha and D.J. Kriegman},
  title = {{E}igenfaces vs. {F}isherfaces: Recognition Using Class Specific
	Linear Projection},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1997},
  volume = {19},
  pages = {711-720},
  number = {7},
  month = {July}
}

@ARTICLE{Bell1995,
  author = {A. J. Bell and T. J. Sejnowski},
  title = {An information-maximization approach to blind separation and blind
	deconvolution},
  journal = {Neural Computation},
  year = {1995},
  volume = {7},
  pages = {1129-1159},
  number = {6}
}

@MISC{Bell2001,
  author = {B. Bell and L. Mass},
  title = {Firms Forge Alliance to Enhance},
  howpublished = {Businessworld},
  month = {29 Dec},
  year = {2001}
}

@TECHREPORT{Bergen1990,
  author = {J.R. Bergen and R. Hingorani},
  title = {Hierarchical Motion-Based Frame Rate Conversion},
  institution = {David Sarnoff Research Center, Princeton},
  year = {1990},
  owner = {sir02mz},
  timestamp = {2008.04.13}
}

@TECHREPORT{Bilmes1998,
  author = {J. Bilmes},
  title = {A gentle tutorial on the {EM} algorithm and its application to parameter
	estimation for {G}aussian mixture and hidden {M}arkov models},
  institution = {University of Berkeley, CA},
  year = {1998},
  number = {ICSI-TR-97-021}
}

@ARTICLE{Blanz2003,
  author = {Volker Blanz and Thomas Vetter},
  title = {Face Recognition Based on Fitting a {3D} Morphable Model},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2003},
  volume = {25},
  pages = {1063-1074},
  number = {9},
  month = {September},
  owner = {sir02mz},
  timestamp = {2008.04.14}
}

@CONFERENCE{Blanz1999,
  author = {V. Blanz and T. Vetter},
  title = {A Morphable Model for the Synthesis of {3D} Faces},
  booktitle = {Proceedings of the SIGGRAPH'99},
  year = {1999},
  pages = {187-194},
  month = {August}
}

@TECHREPORT{Bledsoe1964,
  author = {W.W. Bledsoe},
  title = {The Model Method in Facial Recognition},
  institution = {Panoramic Research Inc.},
  year = {1964},
  number = {PRI:15},
  address = {Palo Alto, CA}
}

@ARTICLE{Bovik1990,
  author = {A. C. Bovik and M. Clark and W. S. Geisler},
  title = {Multichannel texture analysis using localized spatial filters},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1990},
  volume = {12},
  pages = {55-73}
}

@ARTICLE{Breiman1996,
  author = {L. Breiman},
  title = {Bagging predictors},
  journal = {Machine Learning},
  year = {1996},
  volume = {24},
  pages = {123-140},
  number = {2},
  owner = {Mian},
  timestamp = {2008.07.25}
}

@CONFERENCE{Bylander2006,
  author = {Tom Bylander and Lisa Tate},
  title = {Using Validation Sets to Avoid Overfitting in {AdaBoost}},
  booktitle = {Proceedings of the Nineteenth International Florida Artificial Intelligence
	Research Society Conference},
  year = {2006},
  pages = {544-549}
}

@ARTICLE{Cardoso1996,
  author = {Jean-Francois Cardoso and Antoine Souloumiac},
  title = {Jacobi angles for simultaneous diagonalization},
  journal = {SIAM},
  year = {1996},
  volume = {17},
  pages = {161-164},
  number = {1}
}

@CONFERENCE{Cevikalp2004,
  author = {H. Cevikalp and M. Wilkes},
  title = {Face Recogntion by Using Discriminative Common Vectors},
  booktitle = {Proceedings of International Conference on Pattern Recognition},
  year = {2004}
}

@INPROCEEDINGS{Chai1998,
  author = {D. Chai and K.N. Ngan},
  title = {Locating Facial Region of a Head-and-Shoulders Color Image},
  booktitle = {3rd. International Conference on Face \& Gesture Recognition},
  year = {1998},
  pages = {124-129}
}

@ARTICLE{Chen2000,
  author = {L.F. Chen and H.Y.M. Liao and J.C. Lin and M.T. Ko and G.J. Yu},
  title = {A New {LDA}-based Face Recognition System which can solve the small
	sample size problem},
  journal = {Pattern Recognition},
  year = {2000},
  volume = {33},
  pages = {1713-1726}
}

@INPROCEEDINGS{Cheng1991,
  author = {Y. Cheng and K. Liu and J. Yang and Y. Zhuang and N. Gu},
  title = {Human Face Recognition Method Based on the Statistical Model of Small
	Sample Size},
  booktitle = {SPIE Proceedings on Intelligent Robots and Computer Vision X: Algorithms
	and Technology},
  year = {1991},
  pages = {85-95}
}

@INPROCEEDINGS{Collobert1996,
  author = {M. Collobert and R. Feraud and G. Le Tourneur and O. Benier and J.E.
	Viallet and Y.Mahieux and D. Collobert},
  title = {{LISTEN}: A System for Locating and Tracking Individual Speaker},
  booktitle = {Proceedings of IEEE Conference on Automatic Face and Gesture Recognition},
  year = {1996}
}

@ARTICLE{Cootes2001,
  author = {T.F. Cootes and G.J. Edwards and C.J. Taylor},
  title = {Active Appearance Models},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2001},
  volume = {23},
  pages = {681-685},
  number = {6}
}

@TECHREPORT{Cootes2000,
  author = {T.F. Cootes and C.J. Taylor},
  title = {Statistical Models of Appearance for Computer Vision},
  institution = {University of Manchester},
  year = {2000}
}

@INPROCEEDINGS{Cootes1996,
  author = {T.F. Cootes and C.J. Taylor},
  title = {Locating Faces Using Statistical Features},
  booktitle = {Proceedings of Second International Conference on Automatic Face
	and Gesture Recognition},
  year = {1996},
  pages = {204-209}
}

@ARTICLE{Dai1996,
  author = {Y. Dai and Y. Nakano},
  title = {Face-texture model-based on {SGLD} and its application in face detection
	in a color scene},
  journal = {Pattern Recognition},
  year = {1996},
  volume = {29},
  pages = {1007--1017},
  month = {June}
}

@ARTICLE{Daugman1993,
  author = {J. Daugman},
  title = {High Confidence Visual Recognition of Persons by a Test of Statistical
	Independence},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1993},
  volume = {15},
  pages = {1148-1160},
  month = {November}
}

@ARTICLE{Daugman1985,
  author = {J. Daugman},
  title = {Uncertainty Relation for Resolution in Space, Spatial Frequency and
	Orientation Optimized by Two-dimensional Visual Cortical Filters},
  journal = {Journey of the Optical Society of American A},
  year = {1985},
  volume = {2},
  pages = {1160-1169},
  month = {July},
  abstract = {Two-dimensional spatial linear filters are constrained by general
	uncertaintyrelations that limit their attainable information resolution
	for orientation,spatial frequency, and two-dimensional (2D) spatial
	position. The theoreticallower limit for the joint entropy, or uncertainty,
	of these variables is achieved by an optimal 2D filter family whose
	spatial weighting functionsare generated by exponentiated bivariate
	second-order polynomials withcomplex coefficients, the elliptic generalization
	of the one-dimensionalelementary functions proposed in Gabor's famous
	theory of communication[J. Inst. Electr. Eng. 93, 429 (1946)]. The
	set includes filters with variousorientation bandwidths, spatial-frequency
	bandwidths, and spatial dimensions,favoring the extraction of various
	kinds of information from an image.Each such filter occupies an irreducible
	quantal volume (correspondingto an independent datum) in a four-dimensional
	information hyperspace whoseaxes are interpretable as 2D visual space,
	orientation, and spatial frequency,and thus such a filter set could
	subserve an optimally efficient samplingof these variables. Evidence
	is presented that the 2D receptive-field profiles of simple cells
	in mammalian visual cortex are well described by members of this
	optimal 2D filter family, and thus such visual neurons could be said
	to optimize the general uncertainty relations for joint 2D-spatial-2D-spectralinformation
	resolution. The variety of their receptive-field dimensionsand orientation
	and spatial-frequency bandwidths, and the correlationsamong these,
	reveal several underlying constraints, particularly in width/lengthaspect
	ratio and principal axis organization, suggesting a polar division
	of lab or in occupying the quantal volumes of information hyperspace}
}

@ARTICLE{Daugman1988,
  author = {John G Daugman},
  title = {Complete Discrete {2-D} Gabor Transforms by Neural Networks for Image
	Analysis and Compression},
  journal = {IEEE Transactions on Acoustics, Speech, and Signal Processing},
  year = {1988},
  volume = {36},
  pages = {1169-1179}
}

@BOOK{Davies1990,
  title = {Machine Vision: Theory, Algorithms, Practicalities},
  publisher = {Academic Press},
  year = {1990},
  author = {E. R. Davies}
}

@BOOK{Devijver1982,
  title = {Pattern Recognition: A Statistical Approach},
  publisher = {Prentice-Hall},
  year = {1982},
  editor = {P.A. Devijver and J. Kittler},
  author = {P.A. Devijver and J. Kittler}
}

@ARTICLE{Domingos1997,
  author = {Pedro Domingos and Michael Pazzani},
  title = {On the optimality of the simple Bayesian classifier under zero-one
	loss},
  journal = {Machine Learning},
  year = {1997},
  volume = {29},
  pages = {103-137}
}

@ARTICLE{Drucker1993,
  author = {H. Drucker and R.E. Schapire and P. Y. Simard},
  title = {Boosting Performance in Neural Networks},
  journal = {International Journal of Pattern Recognition and Artificial Intelligence},
  year = {1993},
  volume = {7},
  pages = {705-719}
}

@ARTICLE{Dunn1995,
  author = {D. Dunn and W. Higgins},
  title = {Optimal Gabor filters for texture segmentation},
  journal = {IEEE Transactions on Image Processing},
  year = {1995},
  volume = {4},
  pages = {947--964},
  number = {7},
  month = {July}
}

@ARTICLE{Dunn1994,
  author = {Dennis Dunn and William E. Higgins and Joseph Wakeley},
  title = {Texture Segmentation Using {2-D} {G}abor Elementary Functions},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1994},
  volume = {16},
  pages = {130-149}
}

@INPROCEEDINGS{Edwards1998,
  author = {G.J. Edwards and T.F. Cootes and C.J. Taylor},
  title = {Face Recognition using active appearance models},
  booktitle = {Proceedings of European Conference on Computer Vision},
  year = {1998}
}

@BOOK{Efron1993,
  title = {An Introduction to the Bootstrap},
  publisher = {Chapman and Hall},
  year = {1993},
  author = {B. Efron and K. McKusick},
  owner = {Mian},
  timestamp = {2008.07.25}
}

@CONFERENCE{Fan2004,
  author = {W. Fan and Y.H. Wang and W. Liu and T.N. Tan},
  title = {Combining Null Space-based Gabor Features For Face Recognition},
  booktitle = {Proceedings of International Conference on Pattern Recognition},
  year = {2004}
}

@MISC{Fell2002,
  author = {N. Fell and P. Dempsey},
  title = {Whitehall Dithers on Airport Security},
  howpublished = {Times},
  month = {14 Jan},
  year = {2002}
}

@ARTICLE{Fisher1936,
  author = {R. A. Fisher},
  title = {The Use of Multiple Measurements in Taxonomic Problems},
  journal = {Annals of Eugenics},
  year = {1936},
  volume = {7},
  pages = {179-188}
}

@ARTICLE{Fleuret2004,
  author = {Francois Fleuret},
  title = {Fast Binary Feature Selection with Conditional Mutual Information},
  journal = {Journal of Machine Learning Research},
  year = {2004},
  volume = {5},
  pages = {1531-1555}
}

@INPROCEEDINGS{Foresti2003,
  author = {G.L. Foresti and C. Micheloni and L. Snidaro and C. Marchiol},
  title = {Face Detection for Visual Surveillance},
  booktitle = {12th International Conference on Image Analysis and Processing},
  year = {2003},
  pages = {115},
  abstract = {In this paper, a real-time face detection system for color image sequencesis
	presented. The system applies three different face detection methodsand
	integrates the obtained results to achieve a greater location accuracy.The
	first method localizes the human head through outline analysis, focusingthe
	attention of the system on a small image area. The second, a skin
	color method, is applied to the blobs to find skin regions (e.g.,
	faces, hands,etc.). The third, principal component analysis, is used
	to reduce the dimensionality of the data set and to detect face patterns.
	Finally, the obtained facelocations are fused to increase the detection
	reliability and to avoidfalse detections due to occlusions or unfavourable
	human poses. The proposedapproach is used by a video-based surveillance
	system for monitoring indoorscenes. }
}

@BOOK{Forsyth2003,
  title = {Computer Vision A Modern Approach},
  publisher = {Prentice Hall},
  year = {2003},
  author = {D.A. Forsyth and J. Ponce}
}

@TECHREPORT{Frankel1996,
  author = {C. Frankel and M.J. Swain and V. Athitsos},
  title = {{WebSeer}: An Image Search Engine for the World Wide Web},
  institution = {Computer Science Department, University of Chicago},
  year = {1996},
  number = {TR 96-14}
}

@CONFERENCE{Freund1996,
  author = {Y. Freund and R. Schapire},
  title = {Experiments with a new boosting algorithm},
  booktitle = {Proceedings of the Thirteenth International Conference on Machine
	Learning},
  year = {1996},
  owner = {sir02mz},
  timestamp = {2008.06.06}
}

@ARTICLE{Freund1999,
  author = {Yoav Freund and Robert E. Schapire},
  title = {A Short Introduction to Boosting},
  journal = {Journal of Japanese Society for Artificial Intelligence},
  year = {1999},
  volume = {14},
  pages = {771-780}
}

@INPROCEEDINGS{Freund1995,
  author = {Yoav Freund and Robert E. Schapire},
  title = {A Decision-theoretic Generalization of On-line Learning and An Application
	to Boosting},
  booktitle = {Computational Learning Theory: Eurocolt â?5},
  year = {1995},
  pages = {23-37},
  publisher = {Springer-Verlag}
}

@ARTICLE{Friedman2000,
  author = {J. Friedman and T. Hastie and R. Tibshirani},
  title = {Additive Logistic Regression: A Statistical View of Boosting},
  journal = {The Annals of Statistics},
  year = {2000},
  volume = {28},
  pages = {337-374},
  number = {2}
}

@TECHREPORT{Friedman1998,
  author = {J. Friedman and T. Hastie and R. Tibshirani},
  title = {Additive logistic regression: a statistical view of boosting},
  institution = {Stanford University},
  year = {1998}
}

@BOOK{Fukunaga1990,
  title = {Introduction to Statistical Pattern Recognition},
  publisher = {New York: Academic Press},
  year = {1990},
  author = {K. Fukunaga}
}

@BOOK{Fukunaga1972,
  title = {Introduction to Statistical Pattern Recognition},
  publisher = {New York: Academic},
  year = {1972},
  author = {K. Fukunaga}
}

@ARTICLE{Gallant1990,
  author = {S. I. Gallant},
  title = {Perceptron-based learning algorithms},
  journal = {IEEE Transactions on Neural Networks},
  year = {1990},
  volume = {1},
  pages = {179-191},
  number = {2}
}

@ARTICLE{Galton1888,
  author = {Francis Galton},
  title = {Personal Identification and description},
  journal = {Nature},
  year = {1888},
  volume = {21},
  pages = {173-177},
  month = {June}
}

@ARTICLE{Gauthier2001,
  author = {I. Gauthier and C.A. Nelson},
  title = {The Development of Face Expertise},
  journal = {Cognitive Neuroscience},
  year = {2001},
  volume = {11},
  pages = {219-224}
}

@ARTICLE{Georghiades2001,
  author = {Georghiades, A.S. and Belhumeur, P.N. and Kriegman, D.J.},
  title = {From Few to Many: Illumination Cone Models for Face Recognition under
	Variable Lighting and Pose},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2001},
  volume = {23},
  pages = {643-660}
}

@ARTICLE{Goodall1991,
  author = {C. Goodall},
  title = {Procrustes methods in the statistical analysis of shape},
  journal = {Journal of the Royal Statistical Society B},
  year = {1991},
  volume = {53},
  pages = {285-339},
  number = {2}
}

@MISC{Gorsuch22001,
  author = {John Gorsuch},
  title = {Improved Security Through Technology},
  howpublished = {Overhaul \& Maintenance},
  month = {20 Nov},
  year = {2001}
}

@BOOK{Gough2004,
  title = {An Introduction to {GCC}},
  publisher = {Network Theory Limited},
  year = {2004},
  author = {Brian J. Gough}
}

@INCOLLECTION{Graham1998,
  author = {Daniel B. Graham and Nigel M. Allinson},
  title = {Characterizing Virtual Eigen signatures for General Purpose Face
	Recognition},
  booktitle = {Face Recognition: From Theory to Applications},
  publisher = {NATO ASI Series F, Computer and Systems Sciences},
  year = {1998},
  editor = {H. Wechsler and P. J. Phillips and V. Bruce and F. Fogelman-Soulie
	and T. S. Huang},
  volume = {163},
  pages = {446-456}
}

@INCOLLECTION{Gross2005,
  author = {Ralph Gross},
  title = {Face Databases},
  booktitle = {Handbook of Face Recognition},
  publisher = {Springer},
  year = {2005},
  editor = {S. Li and A.K. Jain},
  address = {New York},
  month = {February}
}

@INPROCEEDINGS{Grove1998,
  author = {A. J. Grove and D. Schuurmans},
  title = {Boosting in the Limit: Maximizing the Margin of Learned Ensembles},
  booktitle = {Proceedings of the Fifteenth National Conference on Artificial Intelligence},
  year = {1998}
}

@PHDTHESIS{Hallinan1995,
  author = {P. Hallinan},
  title = {A Deformable Model for Face Recognition Under Arbitrary Lighting
	Conditions},
  school = {Harvard University},
  year = {1995}
}

@ARTICLE{Hancock2000,
  author = {P.J. Hancock and V. Bruce and A.M. Burton},
  title = {Recognition of Unfamiliar Faces},
  journal = {Trends in Cognitive Sciences},
  year = {2000},
  volume = {4},
  pages = {330-337}
}

@BOOK{Haralick1992,
  title = {Computer and Robot Vision},
  publisher = {Addison-Wesley},
  year = {1992},
  author = {R.M. Haralick and L.G. Shapiro},
  volume = {2},
  owner = {sir02mz},
  timestamp = {2008.04.13}
}

@INPROCEEDINGS{Herpers1999,
  author = {R. Herpers and G. Verghese and K.-H. Lichtenauer and G. Sommer},
  title = {Edge and Keypoint Detection in Facial Regions},
  booktitle = {Proceedings of IEEE International Workshop on Recognition, Analysis,
	and Tracking of Faces and Gestures in Real-Time Systems},
  year = {1999}
}

@ARTICLE{Hjelms2001,
  author = {E. Hjelms and B.K. Low},
  title = {Face Detection: A Survey},
  journal = {Computer Vision and Image Understanding},
  year = {2001},
  volume = {83},
  pages = {236-274},
  number = {3}
}

@INPROCEEDINGS{Hong1998,
  author = {H. Hong and H. Neven and C. von der Malsburg},
  title = {Online Facial Expression Recognition Based on Personalized Galleries},
  booktitle = {Proceedings of International Conference on Automatic Face and Gesture
	Recognition},
  year = {1998}
}

@BOOK{Horn1986,
  title = {Robot Vision},
  publisher = {MIT Press},
  year = {1986},
  author = {B. Horn}
}

@ARTICLE{Horn1981,
  author = {B.K.P. Horn and B.G. Schunck},
  title = {Determing Optical Flow},
  journal = {Artificial Intelligence},
  year = {1981},
  volume = {17},
  pages = {185-203},
  owner = {sir02mz},
  timestamp = {2008.04.13}
}

@INPROCEEDINGS{Huang2004,
  author = {Chang Huang and Haizhou Ai and Bo Wu and Shihong Lao},
  title = {Boosting nested cascade detector for multi-view face detection},
  booktitle = {In Proceedings of International Conference on Pattern Recognition
	2004},
  year = {2004}
}

@CONFERENCE{Huang2003,
  author = {J. Huang and B. Heisele and V. Blanz},
  title = {Component-based Face Recognition with {3D} Morphable Models},
  booktitle = {Proceedings of the 4th International Conference on Audio- and Video-Based
	Biometric Person Authentication, AVBPA 2003},
  year = {2003},
  pages = {27-34},
  address = {Guildford, UK},
  month = {June}
}

@CONFERENCE{Huang2002,
  author = {Rui Huang and Qingshan Liu and Hanqing Lu and Songde Ma},
  title = {Solving the Small Sample Size Problem of {LDA}},
  booktitle = {Proceedings of the 16th International Conference on Pattern Recognition},
  year = {2002},
  volume = {3}
}

@ARTICLE{Hubel1978,
  author = {D. Hubel and T. Wiesel},
  title = {Functional Architecture of Macaque Monkey Visual Cortex},
  journal = {Proceedings of Royal Society on Biology (London)},
  year = {1978},
  volume = {198},
  pages = {1-59}
}

@BOOK{Hunt2006,
  title = {A Guide to {MATLAB}: For Beginners and Experienced Users},
  publisher = {Cambridge University Press},
  year = {2006},
  author = {Brian R. Hunt and Ronald L. Lipsman and Jonathan M. Rosenberg and
	Kevin R. Coombes and John E. Osborn and Garrett J. Stuck},
  month = {July}
}

@ARTICLE{Hyvarinen1999,
  author = {A. Hyvarinen},
  title = {Fast and robust fixed-point algorithms for independent component
	analysis},
  journal = {IEEE Transactions on Neural Networks},
  year = {1999},
  volume = {10},
  pages = {626-634}
}

@BOOK{Hyvarinen2001,
  title = {Independent Component Analysis},
  publisher = {John Wiley \& Sons},
  year = {2001},
  author = {A. Hyvarinen and J Karhunen and E. Oja}
}

@CONFERENCE{Ichikawa2006,
  author = {K. Ichikawa and T. Mita and O. Hori},
  title = {Component-based robust face detection using {A}daBoost and decision
	tree},
  booktitle = {Proceedings of the 7th International Conference on Automatic Face
	and Gesture Recognition, FGR 2006},
  year = {2006},
  abstract = {We present a robust frontal face detection method that enables the
	identification of face positions in images by combining the results
	of a low-resolution whole face and individual face parts classifiers.
	Our approach is to use face parts information and change the identification
	strategy based on the results from individual face parts classifiers.
	These classifiers were implemented based on AdaBoost. Moreover, we
	propose a novel method based on a decision tree to improve performance
	of face detectors for occluded faces. The proposed decision tree
	method distinguishes partially occluded faces based on the results
	from the individual classifies. Preliminarily experiments on a test
	sample set containing non-occluded faces and occluded faces indicated
	that our method achieved better results than conventional methods.
	Actual experimental results containing general images also showed
	better results.}
}

@BOOK{Jain1989,
  title = {Fundamentals of Digital Image Processing},
  publisher = {Prentice-Hall},
  year = {1989},
  author = {A. Jain}
}

@ARTICLE{Jain2000,
  author = {A.K. Jain and P.W. Robert and J. Mao},
  title = {Statistical Pattern Recognition: A Review},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2000},
  volume = {22},
  pages = {4-37},
  number = {1}
}

@ARTICLE{Jain2004,
  author = {A.K. Jain and A. Ross and S. Prabhakar},
  title = {An Introduction to Biometric Recognition},
  journal = {IEEE Transactions on Circuits and Systems for Video Technology},
  year = {2004},
  volume = {14},
  pages = {4-20}
}

@ARTICLE{Jain1991,
  author = {Anil K. Jain and Farshid Farrokhnia},
  title = {Unsupervised texture segmentation using Gabor filters},
  journal = {Pattern Recognition},
  year = {1991},
  volume = {4},
  pages = {1167 - 1186},
  month = {December}
}

@CONFERENCE{Jesorsky2001,
  author = {O. Jesorsky and K. Kirchberg and R. Frischholz.},
  title = {Robust Face Detection Using the {H}ausdorff Distance},
  booktitle = {Proceedings of Third International Conference on Audio- and Video-based
	Biometric Person Authentication},
  year = {2001}
}

@ARTICLE{Jones1987,
  author = {J. Jones and L. Palmer},
  title = {An evaluation of two-dimensional Gabor filter model of simple receptive
	fields in cat strait cortex},
  journal = {Journal of Neurophysiology},
  year = {1987},
  volume = {58},
  pages = {1233-1258}
}

@INPROCEEDINGS{Jones1999,
  author = {Michael J. Jones and James M. Rehg},
  title = {Statistical Color Models with Application to Skin Detection},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
  year = {1999},
  pages = {274-280}
}

@ARTICLE{Kadyrov2001,
  author = {A. Kadyrov and M. Petrou},
  title = {The Trace Transform and Its Applications},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2001},
  volume = {23},
  pages = {811-828},
  number = {8},
  month = {August}
}

@ARTICLE{Kanade1977,
  author = {Takeo Kanade},
  title = {Computer Recognition of Human Faces},
  journal = {Interdisciplinary Systems Research},
  year = {1977},
  volume = {47},
  pages = {1-106},
  abstract = {Pictures o f human faces are successfully analyzed by a computer program
	which extracts face-feature points, such as nose, mouth, eyes and
	so on. The program was tested with more than 800 photographs. Emphasis
	is put on the flexible picture analysis scheme with feedback which
	was first employed in the picture analysis program with remarkable
	success. The program consists of a collection of rather simple subroutines,
	each of which works on the specific part of the picture, and elaborate
	combination of them with backup procedures makes the whole process
	flexible and adaptive. An experiment on face identification of 20
	people was also conducted.}
}

@ARTICLE{Kass1988,
  author = {M. Kass and A. Witkin and D. Terzopoulos},
  title = {Snakes: Active contour models},
  journal = {International Journal of Computer Vision},
  year = {1988},
  volume = {1},
  pages = {321-331},
  number = {4},
  month = {January},
  abstract = {A snake is an energy-minimizing spline guided by external constraint
	forces and influenced by image forces that pull it toward features
	such as lines and edges. Snakes are active contour models: they lock
	onto nearby edges, localizing them accurately. Scale-space continuation
	can be used to enlarge the capture region surrounding a feature.
	Snakes provide a unified account of a number of visual problems,
	including detection of edges, lines, and subjective contours; motion
	tracking; and stereo matching. We have used snakes successfully for
	interactive interpretation, in which user-imposed constraint forces
	guide the snake near features of interest.}
}

@INPROCEEDINGS{Kaya1972,
  author = {Y. Kaya and K. Kobayashi},
  title = {A Basic Study on Human Face Recognition},
  booktitle = {Frontiers of Pattern Recognition},
  year = {1972},
  editor = {S. Wantanabe},
  pages = {265-289},
  publisher = {New York: Academic}
}

@ARTICLE{Kearns1994,
  author = {Michael Kearns and Leslie G. Valiant},
  title = {Cryptographic Limitations on Learning Boolean Formula and Finite
	Automata},
  journal = {Journal of the Association for Computing Machinery},
  year = {1994},
  volume = {41},
  pages = {67-95}
}

@TECHREPORT{Kelly1970,
  author = {M.D. Kelly},
  title = {Visual Identification of People by Computer},
  institution = {Stanford University},
  year = {1970},
  type = {Stanford AI Project},
  number = {AI-130}
}

@ARTICLE{Keys1981,
  author = {R. Keys},
  title = {Cubic convolution interpolation for digital image processing},
  journal = {IEEE Transactions on Signal Processing, Acoustics, Speech, and Signal
	Processing},
  year = {1981},
  volume = {29},
  pages = {1153-1160},
  number = {6},
  month = {December}
}

@ARTICLE{Kirby1990,
  author = {M. Kirby and L. Sirovich},
  title = {Application of the Karhunen-Loeve procedure for the characterization
	of human faces},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1990},
  volume = {12},
  pages = {103-108},
  number = {1},
  month = {Jan}
}

@INPROCEEDINGS{Kohavi1995,
  author = {Ron Kohavi},
  title = {A study of cross-validation and bootstrap for accuracy estimation
	and model selection},
  booktitle = {Proceedings of the Fourteenth International Joint Conference on Artificial
	Intelligence},
  year = {1995}
}

@CONFERENCE{Kong2006,
  author = {Hui Kong and Xuchun Li and Jian-Gang Wang and Chandra Kambhamettu},
  title = {Ensemble {LDA} for Face Recognition},
  booktitle = {Proceedings of the International Conference on Biometrics Authentication
	(ICBA)},
  year = {2006}
}

@CONFERENCE{Kong2005,
  author = {H. Kong and L. Wang and E. Teoh and J. Wang and R. Venkateswarlu},
  title = {A framework of {2D} Fisher discriminant analysis: Application to
	face recognition with small number of training samples},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2005}
}

@PHDTHESIS{Krueger2001,
  author = {Volker Krueger},
  title = {Gabor Wavelet Networks for Object Representation},
  school = {Christian-Albrechts University, Kiel, Germany},
  year = {2001}
}

@INPROCEEDINGS{Kruger2000,
  author = {V. Kruger},
  title = {Gabor wavelet network for Object representation},
  booktitle = {Proceedings of International Dagstuhl Workshop},
  year = {2000}
}

@INPROCEEDINGS{Kumar2000,
  author = {V. Kumar and T. Poggio},
  title = {Learning-based Approach to Real Time Tracking and Analysis of Faces},
  booktitle = {Proceedings of Fourth IEEE International Conference on Automatic
	Face and Gesture Recognition},
  year = {2000},
  pages = {96 - 101},
  month = {March},
  abstract = {This paper describes a trainable system capable of tracking faces
	and facial features like eyes and nostrils and estimating basic mouth
	features such as degrees of openness and smile in real time. In developing
	this system, we have addressed the twin issues of image representation
	and algorithms for learning. We have used the invariance properties
	of image representations based on Haar wavelets to robustly capture
	various facial features. Similarly, unlike previous approaches this
	system is entirely trained using examples and does not rely on a
	priori (hand-crafted) models of facial features based on an optical
	flow or facial musculature. The system works in several stages that
	begin with face detection, followed by localization of facial features
	and estimation of mouth parameters. Each of these stages is formulated
	as a problem in supervised learning from examples. We apply the new
	and robust technique of support vector machines (SVM) for classification
	in the stage of skin segmentation, face detection and eye detection.
	Estimation of mouth parameters is modeled as a regression from a
	sparse subset of coefficients (basis functions) of an overcomplete
	dictionary of Haar wavelets}
}

@INPROCEEDINGS{Kwon1994,
  author = {Y. Kwon and N. Da Vitoria Lobo},
  title = {Face detection using templates},
  booktitle = {International Conference on Pattern Recognition},
  year = {1994},
  pages = {764-767}
}

@ARTICLE{Lades1993,
  author = {M. Lades and J. Vorbruggen and J. Buhmann and J. Lange and C.V.D.
	Malsburg and R. Wurtz},
  title = {Distortion Invariant Object Recognition on the Dynamic Link Architecture},
  journal = {IEEE Transactions on Computers},
  year = {1993},
  volume = {42},
  pages = {300-311}
}

@TECHREPORT{Landre2003,
  author = {Jerome Landre},
  title = {Programming with {I}ntel {IPP} and {Intel} {OpenCV} under {GNU} {L}inux:
	A Beginner's Tutorial},
  institution = {Universite de Bourgogne},
  year = {2003}
}

@ARTICLE{Lanitis1995,
  author = {A. Lanitis and C.J. Taylor, and T.F. Cootes},
  title = {An Automatic Face Identification System Using Flexible Appearance
	Models},
  journal = {Image and Vision Computing},
  year = {1995},
  volume = {13},
  pages = {393-401},
  number = {5},
  month = {June}
}

@ARTICLE{Lanitis1997,
  author = {A. Lanitis and C.J. Taylor and T.F. Cootes},
  title = {Automatic Interpretation and Coding of Face Images Using Flexible
	Models},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1997},
  volume = {19},
  pages = {743-756},
  number = {7}
}

@ARTICLE{Lee1996a,
  author = {C.H. Lee and J.S. Kim and K.H. Park},
  title = {Automatic Human Face Location in A Complex Background},
  journal = {Pattern Recognition},
  year = {1996},
  volume = {29},
  pages = {1877-1889}
}

@ARTICLE{Lee1996,
  author = {T. Lee},
  title = {Image Representation using {2D} Gabor wavelets},
  journal = {IEEE Transaction on Pattern Analysis and Machine Intelligence},
  year = {1996},
  volume = {18},
  pages = {959-971}
}

@INPROCEEDINGS{Leung1995,
  author = {T.K. Leung and M. C. Burl and P. Perona},
  title = {Finding faces in cluttered scenes using random labelled graph matching},
  booktitle = {Fifth International Conference on Computer Vision},
  year = {1995},
  pages = {637-644},
  month = {June},
  key = {BuLePe295}
}

@ARTICLE{LiStan2004,
  author = {Stan Z. Li and ZhenQiu Zhang},
  title = {{FloatBoost} Learning and Statistical Face Detection},
  journal = {IEEE Transactions on Pattern Analysis and Machine Learning},
  year = {2004},
  volume = {26},
  pages = {1112-1123},
  number = {9}
}

@ARTICLE{Li1990,
  author = {Wentian Li},
  title = {Mutual Information Functions Versus Correlation Functions},
  journal = {Journal of Statistical Physics},
  year = {1990},
  volume = {60},
  pages = {823-837}
}

@INPROCEEDINGS{Li2004,
  author = {Z. Li and X. Tang},
  title = {Bayesian Face Recognition Using Support Vector Machine and Face Clustering},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2004},
  pages = {374-380}
}

@ARTICLE{Liao2001,
  author = {Ping Sung Liao and Tse Sheng Chen and Pau Choo Chung},
  title = {A Fast Algorithm for Multilevel Thresholding},
  journal = {Journal of Information Science and Engineering},
  year = {2001},
  volume = {17},
  pages = {713-727}
}

@ARTICLE{Liu2004,
  author = {C. Liu},
  title = {Gabor-Based Kernel PCA with Fractional Power Polynomial Models for
	Face Recognition},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2004},
  volume = {26},
  pages = {572-581}
}

@ARTICLE{Liu2004smc,
  author = {C. Liu},
  title = {Enhanced Independent Component Analysis and Its Application to Content
	Based Face Image Retrieval},
  journal = {IEEE Transactions on Systems, Man, and Cybernetics- Part B: Cybernetics},
  year = {2004},
  volume = {34},
  pages = {1117-1127},
  number = {2},
  month = {April}
}

@ARTICLE{Liu2003,
  author = {C. Liu and H. Wechsler},
  title = {Independent Component Analysis of Gabor Features for Face Recognition},
  journal = {IEEE Transactions on Neural Networks},
  year = {2003},
  volume = {14},
  pages = {919-928}
}

@ARTICLE{Liu2002,
  author = {C. Liu and H. Wechsler},
  title = {Gabor Feature Based Classification Using Enhanced Fisher Linear Discriminant
	Model for Face Recognition},
  journal = {IEEE Transactions on Image Processing},
  year = {2002},
  volume = {11},
  pages = {467-476}
}

@CONFERENCE{Liu2001,
  author = {Chengjun Liu and Harry Wechsler},
  title = {A Gabor Feature Classifier for Face Recognition},
  booktitle = {Proceedings of the Eighth International Conference on Computer Vision
	(ICCV'01)},
  year = {2001},
  volume = {2}
}

@BOOK{Loeve1955,
  title = {Probability Theory},
  publisher = {Princeton N.J},
  year = {1955},
  editor = {Van Nostrand},
  author = {M. M. Loeve}
}

@ARTICLE{Lu2003,
  author = {J. Lu and K.N. Plataniotis and A.N. Venetsanopoulos},
  title = {Face Recognition Using {LDA}-Based Algorithms},
  journal = {IEEE Transactions on Neural Networks},
  year = {2003},
  volume = {14},
  pages = {195-200},
  number = {1},
  month = {January}
}

@PHDTHESIS{Lu2006,
  author = {Xiaoguang Lu},
  title = {{3D} Face Recognition across Pose and Expression},
  school = {Michigan State University},
  year = {2006}
}

@CONFERENCE{Lu2003fusion,
  author = {X.G. Lu and Y.H. Wang and A.K. Jain},
  title = {Combining Classifiers for Face Recognition},
  booktitle = {Proceedings of IEEE International Conference on Multimedia and Expo},
  year = {2003},
  volume = {3},
  pages = {13-16}
}

@ARTICLE{Lyons1999,
  author = {M.J. Lyons and J. Budynek and S. Akamatsu},
  title = {Automatic Classification of Single Facial Image},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1999},
  volume = {21},
  pages = {1357-1362}
}

@MISC{Ma2001,
  author = {J. Ma and Y. Zhao and S. Ahalt and D. Eads},
  title = {{OSU} {SVM}: A Support Vector Machine Toolbox for {M}atlab},
  howpublished = {Online},
  year = {2001},
  timestamp = {2008.01.31},
  url = {http://svm.sourceforge.net/license.shtml}
}

@ARTICLE{Manjunath1996,
  author = {B.S. Manjunath and W.Y. Ma},
  title = {Texture Features For Browsing and Retrieval of Image Data},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1996},
  volume = {18},
  pages = {837-842},
  number = {8},
  month = {August}
}

@ARTICLE{Martinez2001,
  author = {Aleix Martinez and Avinash Kak},
  title = {{PCA} versus {LDA}},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2001},
  volume = {23},
  pages = {228-233}
}

@TECHREPORT{Mason1999,
  author = {L. Mason and J. Baxter and P. Bartlett and M. Frean},
  title = {Boosting algorithm as gradient descent in function space},
  institution = {Department of Systems Engineering, Australian National Univeristy},
  year = {1999},
  owner = {sir02mz},
  timestamp = {2008.06.06}
}

@CONFERENCE{Matas2000,
  author = {J. Matas and M. Hamous and K. Jonsson},
  title = {Comparison of Face Verification Results on the XM2VTS Database},
  booktitle = {Proceedings of the International Conference on Pattern Recognition},
  year = {2000}
}

@TECHREPORT{Matas2004,
  author = {Jiri Matas and Jan Sochman},
  title = {AdaBoost},
  institution = {Centre for Machine Perception, Czech Technical University, Prague},
  year = {2004}
}

@ARTICLE{Mavroforakis2006,
  author = {M.E. Mavroforakis and S. Theodoridis},
  title = {A geometric approach to Support Vector Machine ({SVM}) classification},
  journal = {IEEE Transactions on Neural Networks},
  year = {2006},
  volume = {17},
  pages = {671-682},
  owner = {Mian},
  timestamp = {2008.08.27}
}

@ARTICLE{Maybank2004,
  author = {S.J. Maybank},
  title = {Detection of Image Structure using the Fisher Information and the
	Rao Metric},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2004},
  volume = {26},
  pages = {1579- 1589},
  number = {12},
  month = {December}
}

@ARTICLE{McKenna1998,
  author = {S. McKenna and S. Gong and Y. Raja},
  title = {Modelling facial colour and identity with gaussian mixtures},
  journal = {Pattern Recognition},
  year = {1998},
  volume = {31},
  pages = {1883-1892},
  number = {12}
}

@INPROCEEDINGS{Messer1999,
  author = {K. Messer and J. Matas and J. Kittler and K. Jonsson},
  title = {{XM2VTSDB}: The Extended {M2VTS} Database},
  booktitle = {Audio- and Video-based Biometric Person Authentication, AVBPA'99},
  year = {1999},
  pages = {72-77},
  address = {Washington, D.C.},
  month = {March},
  note = {16 IDIAP--RR 99-02}
}

@BOOK{Michel1963,
  title = {Probability Theory },
  publisher = {D. Van Nostrand Company, Inc},
  year = {1963},
  author = {Loeve Michel}
}

@BOOK{Michie1994,
  title = {Machine Learning, Neural and Statistical Classification},
  publisher = {Ellis Horwood Upper Saddle River},
  year = {1994},
  author = {D Michie and D.J. Spiegelhalter and C.C. Taylor},
  address = {NJ, USA}
}

@INPROCEEDINGS{Ming2000,
  author = {Hsuan Yang Ming and N. Abuja and D. Kriegman},
  title = {Face detection using mixtures of linear subspaces},
  booktitle = {Fourth {IEEE} International Conference on Automatic Face and Gesture
	Recognition},
  year = {2000},
  pages = {70-76}
}

@ARTICLE{Moghaddam2002,
  author = {B. Moghaddam},
  title = {Principal Manifolds and Probabilistic Subspaces for Visual Recognition},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2002},
  volume = {24},
  pages = {780-788}
}

@ARTICLE{Moghaddam2000,
  author = {B. Moghaddam and T. Jebara and A. Pentland},
  title = {Bayesian Face Recognition},
  journal = {Pattern Recognition},
  year = {2000},
  volume = {33},
  pages = {1771-1782},
  month = {November}
}

@ARTICLE{Moghaddam1997,
  author = {B. Moghaddam and A. Pentland},
  title = {Probabilistic Visual Learning for Object Representation},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1997},
  volume = {19},
  pages = {696-710},
  number = {7},
  month = {July},
  abstract = {We present an unsupervised technique for visual learning, which is
	based on density estimation in high-dimensional spaces using an eigenspace
	decomposition. Two types of density estimates are derived for modeling
	the training data: a multivariate Gaussian (for unimodal distributions)
	and a mixture-of-Gaussians model (for multimodal distributions).
	Those probability densities are then used to formulate a maximum-likelihood
	estimation framework for visual search and target detection for automatic
	object recognition and coding. Our learning technique is applied
	to the probabilistic visual modeling, detection, recognition, and
	coding of human faces and nonrigid objects, such as hands}
}

@BOOK{Morrison1990,
  title = {Multivariate Statistical Methods},
  publisher = {McGraw-Hill, New York},
  year = {1990},
  author = {D.F. Morrison}
}

@CONFERENCE{Nefian2000,
  author = {A. Nefian and M. Hayes},
  title = {Maximum likelihood training of the embedded {HMM} for face detection
	and recognition},
  booktitle = {Proceedings of the IEEE International Conference on Image Processing,
	ICIP 2000},
  year = {2000},
  volume = {1},
  pages = {33-36},
  address = {Vancouver, BC, Canada},
  month = {September}
}

@CONFERENCE{Nefian1998,
  author = {A. Nefian and M. Hayes},
  title = {Hidden Markov Models for Face Recognition},
  booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech,
	and Signal Processing, ICASSP'98},
  year = {1998},
  volume = {5},
  pages = {2721-2724},
  month = {May}
}

@ARTICLE{Ojala2002,
  author = {Timo Ojala and Matti Pietikainen and Topi Maenpaa},
  title = {Multiresolution Gray-Scale and Rotation Invariant Texture Classification
	with Local Binary Patterns},
  journal = {IEEE Transcations on Pattern Analysis and Machine Intelligence},
  year = {2002},
  volume = {24},
  pages = {971-987},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@ARTICLE{Oliver2000,
  author = {N. Oliver and A. Pentland and F. Berard},
  title = {{LAFTER}: a real-time face and lips tracker with facial expression
	recognition},
  journal = {Pattern Recognition},
  year = {2000},
  volume = {33},
  pages = {1369--1382}
}

@ARTICLE{Olshausen1996,
  author = {B. Olshausen and D. Field},
  title = {Emergence of Simple-cell Receptive Field Properties by Learning a
	Sparse Code for Natural Images},
  journal = {Nature},
  year = {1996},
  volume = {381},
  pages = {607-609}
}

@ARTICLE{Opitz1999,
  author = {David Opitz and Richard Maclin},
  title = {Popular Ensemble Methods: An Empirical Study},
  journal = {Journal of Artificial Intelligence Research},
  year = {1999},
  volume = {11},
  pages = {169-198},
  owner = {sir02mz},
  timestamp = {2008.06.06}
}

@INPROCEEDINGS{Osuna1997,
  author = {E. Osuna and R. Freund and F. Girosi},
  title = {Training Support Vector Machines: An Application to Face Detection},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {1997},
  pages = {130-136},
  month = {June},
  abstract = {We investigate the application of Support Vector Machines (SVMs) in
	computer vision. SVM is a learning technique developed by V. Vapnik
	and his team (AT&T Bell Labs., 1985) that can be seen as a new method
	for training polynomial, neural network, or Radial Basis Functions
	classifiers. The decision surfaces are found by solving a linearly
	constrained quadratic programming problem. This optimization problem
	is challenging because the quadratic form is completely dense and
	the memory requirements grow with the square of the number of data
	points. We present a decomposition algorithm that guarantees global
	optimality, and can be used to train SVM's over very large data sets.
	The main idea behind the decomposition is the iterative solution
	of sub-problems and the evaluation of optimality conditions which
	are used both to generate improved iterative values, and also establish
	the stopping criteria for the algorithm. We present experimental
	results of our implementation of SVM, and demonstrate the feasibility
	of our approach on a face detection problem that involves a data
	set of 50,000 data points}
}

@ARTICLE{Otsu1979,
  author = {N. Otsu},
  title = {A threshold selection method from gray level histograms},
  journal = {IEEE Transactions on Systems, Man and Cybernetics},
  year = {1979},
  volume = {9},
  pages = {62-66},
  month = {March},
  note = {minimize inter class variance},
  keywords = {threshold selection}
}

@INPROCEEDINGS{Pelleg2000,
  author = {D. Pelleg and A. Moore},
  title = {X-means: Extending {K}-means with efficient estimation of the number
	of the clusters},
  booktitle = {Proceedings of International Conference on Machine Learning},
  year = {2000}
}

@ARTICLE{Penev1996,
  author = {P. S. Penev and J. J. Atick},
  title = {Local feature analysis: A general statistical theory for object representation},
  journal = {Neural Systems},
  year = {1996},
  volume = {7},
  pages = {477-500}
}

@ARTICLE{Peng2005,
  author = {Hanchuan Peng and Fuhui Long and Chris Ding},
  title = {Feature Selection Based on Mutual Information: Criteria of Max-Dependency,
	Max-Relevance, and Min-Redundancy},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2005},
  volume = {27},
  pages = {1226-1238}
}

@INPROCEEDINGS{Pentland1994,
  author = {A. Pentland and B. Moghaddam and T. Starner},
  title = {View-based and Modular Eigenspaces for Face Recognition},
  booktitle = {In Proceedings of IEEE Conference on Computer Vision and Pattern
	Recognition},
  year = {1994}
}

@CONFERENCE{Phillips1997,
  author = {P.J. Phillips and H. Moon and P. Rauss and S.A. Rizvi},
  title = {The {FERET} Methodology for Face Recognition Algorithm},
  booktitle = {Proceedings of the International Conference on Computer Vision and
	Pattern Recognition},
  year = {1997},
  pages = {137-143}
}

@ARTICLE{Phillips1998,
  author = {P.J. Phillips and H. Wechsler and J. Huang and P.J. Rauss},
  title = {The {FERET} Database and Evaluation Procedure for Face Recognition
	Algorithm},
  journal = {Image and Vision Computing},
  year = {1998},
  volume = {16},
  pages = {295-306},
  number = {5}
}

@ARTICLE{Phillips2000,
  author = {P. Jonathon Phillips and Hyeonjoon Moon and Syed A. Rizvi and Patrick
	J.Rauss},
  title = {The {FERET} Evaluation Methodology for Face-Recognition Algorithms},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2000},
  volume = {22},
  pages = {1090-1104},
  number = {10},
  month = {October}
}

@TECHREPORT{Phillips1996,
  author = {P. Jonathon Phillips and Patrick J. Rauss and Sandor Z. Der},
  title = {{FERET} (Face Recognition Technology) Recognition Algorithm Development
	and Test Results},
  institution = {Army Research Lab},
  year = {1996}
}

@ARTICLE{Pope2001,
  author = {Chris Pope},
  title = {Ways to Keep the Terrorist Grounded},
  journal = {Professional Engineering},
  year = {2001},
  volume = {14},
  pages = {20-21}
}

@BOOK{Press1992,
  title = {Numerical Recipes in {C}},
  publisher = {Cambridge University Press},
  year = {1992},
  author = {W.H. Press and S.A. Teukolsky and W.T. Vetterling and B.P. Flannery},
  owner = {sir02mz},
  timestamp = {2008.04.13}
}

@ARTICLE{Pudil1994,
  author = {P. Pudil and J. Novovicova and J. Kittler},
  title = {Floating Search methods in feature selection},
  journal = {Pattern Recognition Letters},
  year = {1994},
  volume = {11},
  pages = {1119-1125},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@TECHREPORT{Martinez1998,
  author = {A. R.Martinez and R. Benavente},
  title = {The {AR} face database},
  institution = {Computer Vision Center},
  year = {1998},
  number = {24}
}

@ARTICLE{Rao1995,
  author = {R. Rao and D. Ballard},
  title = {An Active Vision Architecture based on Iconic Representations},
  journal = {Artificial Intelligence},
  year = {1995},
  volume = {78},
  pages = {461-505}
}

@ARTICLE{Ratsch2002,
  author = {Gunnar Ratsch and Sebastian Mika and Bernhard Scholkopf and Klaus-Robert
	Muller},
  title = {Constructing Boosting Algorithms from {SVMs}: An Application to One-Class
	Classification},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2002},
  volume = {24},
  pages = {1184 - 1199}
}

@ARTICLE{Raudys1991,
  author = {S. Raudys and A. Jain},
  title = {Small Sample Size Effects in Statistical Pattern Recognition: Recommendations
	for Practitioners},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1991},
  volume = {13},
  pages = {252-264},
  number = {3}
}

@CONFERENCE{Riedmiller1993,
  author = {M. Riedmiller and H. Braun},
  title = {A Direct Adaptive Method for Faster Backpropagation Learning: The
	{RPROP} Algorithm},
  booktitle = {Proceeding of International Conference on Neural Network},
  year = {1993}
}

@BOOK{Ripley1996,
  title = {Pattern Recognition and Neural Networks},
  publisher = {Cambridge University Press},
  year = {1996},
  author = {B. Ripley}
}

@CONFERENCE{Rizvi1998,
  author = {S.A. Rizvi and P.J. Phillips and H. Moon},
  title = {A Verification Protocol and Statistical Performance Analysis for
	Face Recognition Algorithm},
  booktitle = {Proceedings of the International Conference on Computer Vision and
	Pattern Recognition},
  year = {1998},
  pages = {833-838}
}

@CONFERENCE{Rizvi1998fg,
  author = {S.A. Rizvi and P.J. Phillips and H. Moon},
  title = {The {FERET} Verification Testing Protocol for Face Recognition Algorithm},
  booktitle = {Proceedings of the International Conference on Automatic Face and
	Gesture Recognition},
  year = {1998},
  number = {48-53}
}

@ARTICLE{Rosenblatt1958,
  author = {Frank Rosenblatt},
  title = {The Perceptron: A Probabilistic Model for Information Storage and
	Organization in the Brain},
  journal = {Psychological Review},
  year = {1958},
  volume = {65},
  pages = {3860408}
}

@INPROCEEDINGS{Rowley1998,
  author = {H. Rowley and S. Baluja and T. Kanade},
  title = {Rotation Invariant Neural Network-Based Face Detection},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {1998},
  pages = {38-44},
  month = {June}
}

@ARTICLE{Rowley1998a,
  author = {H. Rowley and S. Baluja and T. Kanade},
  title = {Neural network-based face detection},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1998},
  volume = {20},
  pages = {23-38},
  month = {Jan},
  abstract = {We present a neural network-based upright frontal face detection system.
	A retinally connected neural network examines small windows of an
	image and decides whether each window contains a face. The system
	arbitrates between multiple networks to improve performance over
	a single network. We present a straightforward procedure for aligning
	positive face examples for training. To collect negative examples,
	we use a bootstrap algorithm, which adds false detections into the
	training set as training progresses. This eliminates the difficult
	task of manually selecting nonface training examples, which must
	be chosen to span the entire space of nonface images. Simple heuristics,
	such as using the fact that faces rarely overlap in images, can further
	improve the accuracy. Comparisons with several other state-of-the-art
	face detection systems are presented, showing that our system has
	comparable performance in terms of detection and false-positive rates}
}

@ARTICLE{Sahoo1988,
  author = {P.K. Sahoo and S. Soltani and A.K. Wong and Y.C. Chan},
  title = {A survey of thresholding techniques},
  journal = {Computer Vision, Graphics and Image Processing},
  year = {1988},
  volume = {41},
  pages = {233-260}
}

@INPROCEEDINGS{Sakai1972,
  author = {T. Sakai and M. Nagao and T. Kanade},
  title = {Computer Analysis and Classification of Photographs of Human Faces},
  booktitle = {First USA-JAPAN Computer Conference},
  year = {1972},
  pages = {55-62}
}

@PHDTHESIS{samaria94face,
  author = {F.S. Samaria},
  title = {Face Recognition Using Hidden Markov Models},
  school = {University of Cambridge},
  year = {1994}
}

@INPROCEEDINGS{Samaria1994,
  author = {Ferdinando S. Samaria and Andy C. Harter},
  title = {Parameterisation of a Stochastic Model for human Face Identification},
  booktitle = {IEEE 2nd Workshop on Applications of Computer Vision},
  year = {1994},
  pages = {138{\"i}142},
  address = {Sarasota (Florida)},
  month = {December}
}

@ARTICLE{Satoh1999,
  author = {S. Satoh and Y. Nakamura and T. Kanade},
  title = {{Name-It}: Naming and Detecting Faces in News Videos},
  journal = {IEEE Multimedia},
  year = {1999},
  volume = {6},
  pages = {22-35},
  number = {6},
  month = {Jan-Mar},
  abstract = {We developed Name-It, a system that associates faces and names in
	news videos. It processes information from the videos and can infer
	possible name candidates for a given face or locate a face in news
	videos by name. To accomplish this task, the system takes a multimodal
	video analysis approach: face sequence extraction and similarity
	evaluation from videos, name extraction from transcripts, and video-caption
	recognition}
}

@INPROCEEDINGS{Saxe1996a,
  author = {D. Saxe and R. Foulds},
  title = {Toward Robust Skin Identification in Video Images},
  booktitle = {Proceedings of Second International Conference on Automatic Face
	and Gesture Recognition},
  year = {1996},
  pages = {379-384}
}

@ARTICLE{Schapire1990,
  author = {R.E. Schapire},
  title = {The strength of weak learnability},
  journal = {Machine Learning},
  year = {1990},
  volume = {5},
  pages = {197-227},
  number = {2}
}

@CONFERENCE{Schapire1997,
  author = {R. Schapire and Y. Freund and P. Bartlett and W. Lee},
  title = {Boosting the margin: A new explanation for the effectiveness of voting
	methods},
  booktitle = {Proceedings of the Fourteenth International Conference on Machine
	Learning},
  year = {1997},
  owner = {sir02mz},
  timestamp = {2008.06.06}
}

@INPROCEEDINGS{Schapire1998,
  author = {R.E. Schapire and Y. Singer},
  title = {Improved Boosting Algorithms Using Confidence-Rated Predictions},
  booktitle = {Proceedings of The 11th Annal Conference on Computational Learning
	Theory},
  year = {1998},
  number = {80-91}
}

@INPROCEEDINGS{Schapire1999,
  author = {Robert E. Schapire},
  title = {A Brief Introduction to Boosting},
  booktitle = {Proceedings of the Sixteenth International Joint Conference on Artificial
	Intelligence},
  year = {1999}
}

@ARTICLE{Schapire1999ml,
  author = {R. E. Schapire and Y. Singer},
  title = {Improved Boosting Algorithm using Confidence-rated Predictions},
  journal = {Machine Learning},
  year = {1999},
  volume = {37},
  pages = {297-336},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@ARTICLE{Schiele2000,
  author = {B. Schiele and J. Crowley},
  title = {Recognition without Correspondence using Multi-dimensional Receptive
	Field Histograms},
  journal = {International Journal on Computer Vision},
  year = {2000},
  volume = {36},
  pages = {31-52}
}

@INPROCEEDINGS{Schneiderman2000,
  author = {H. Schneiderman and T. Kanade},
  title = {A Statistical Method for {3D} Object Detection Applied to Faces and
	Cars},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2000},
  volume = {1},
  pages = {746-751}
}

@INPROCEEDINGS{Schneiderman1998,
  author = {H. Schneiderman and T. Kanade},
  title = {Probabilistic Modeling of Local Appearance and Spatial Relationship
	for Object Recognition},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {1998},
  pages = {45-51}
}

@ARTICLE{Scholkopf1998,
  author = {B. Scholkopf and A. Smola and K.R. Muller},
  title = {Nonlinear Component Analysis as a Kernel Eigenvalue Problem},
  journal = {Neural Computation},
  year = {1998},
  volume = {10},
  pages = {1299-1319}
}

@CONFERENCE{Shan2005,
  author = {Caifeng Shan and Shaogang Gong and Peter W. McOwan},
  title = {Conditional Mutual Information Based Boosting for Facial Expression
	Recognition},
  booktitle = {Proceedings of British Machine Vision Conference},
  year = {2005}
}

@PHDTHESIS{Shashua1994,
  author = {A. Shashua},
  title = {Geometry and Photometry in {3D} Visual Recognition},
  school = {Massachusetts Institute of Technology},
  year = {1994}
}

@ARTICLE{Shen2006,
  author = {Linlin Shen and Li Bai},
  title = {{MutualBoost} learning for selecting Gabor features for face recognition},
  journal = {Pattern Recognition Letters},
  year = {2006},
  volume = {27},
  pages = {1758-1767}
}

@CONFERENCE{Shen2005,
  author = {Linlin Shen and Li Bai and Bardsley Daniel and Yangsheng Wang},
  title = {Gabor Feature Selection for Face Recognition using Improved {A}daBooost
	Learning},
  booktitle = {Proceedings of International workshop on biometric recognition systems},
  year = {2005},
  owner = {Mian},
  timestamp = {2008.08.15}
}

@ARTICLE{Sim2003,
  author = {T. Sim and S. Baker and M. Bsat},
  title = {The {CMU} Pose, Illumination, and Expression Database},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2003},
  volume = {25},
  pages = {1615-1618},
  number = {12},
  month = {December}
}

@ARTICLE{Sinha2006,
  author = {Pawan Sinha and Benjamin Balas and Yuri Ostrovsky and Richard Russell},
  title = {Face Recognition by Humans: Nineteen Results All Computer Vision
	Researchers Should Know About},
  journal = {Proceedings of The IEEE},
  year = {2006},
  volume = {94},
  pages = {1948-1962},
  number = {11},
  month = {November}
}

@TECHREPORT{Sirohey1993,
  author = {Saad Ahmed Sirohey},
  title = {Human Face Segmentation and Identification},
  institution = {University of Maryland},
  year = {1993},
  number = {CS-TR-317}
}

@ARTICLE{Snow2002,
  author = {C. Snow and H. Nguyen and V. S. Pande and M. Gruebele},
  title = {Absolute comparison of simulated and experimental protein-folding
	dynamics},
  journal = {Nature},
  year = {2002},
  volume = {420},
  pages = {102-106},
  number = {6911}
}

@INCOLLECTION{Sollich1995,
  author = {P. Sollich and A. Krogh},
  title = {Learning with ensembles: How over-fitting can be useful},
  booktitle = {Advances in Neural Information Processing Systems},
  publisher = {MIT Press},
  year = {1995},
  editor = {D. Touretsky and M. Mozer and M. Hasselmo},
  volume = {8},
  pages = {190-196}
}

@BOOK{Sonka1998,
  title = {Image Processing, Analysis, and Machine Vision},
  publisher = {Thomson-Engineering},
  year = {1998},
  author = {Milan Sonka and Vaclav Hlavac and Roger Boyle},
  month = {September}
}

@CONFERENCE{Srisuk2003EE,
  author = {S. Srisuk and W. Kurutach},
  title = {Face Recognition using a New Texture Representation of Face Images},
  booktitle = {Proceedings of Electrical Engineering Conference},
  year = {2003},
  pages = {1097-1102},
  address = {Cha-am, Thailand},
  month = {November}
}

@CONFERENCE{Srisuk2003,
  author = {S. Srisuk and M. Petrou and W. Kurutach and A. Kadyrov},
  title = {Face Authentication using the Trace Transform},
  booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision
	and Pattern Recognition (CVPR'03)},
  year = {2003},
  pages = {305-312},
  address = {Madison, Wisconsin, USA},
  month = {June}
}

@ARTICLE{Sung1996,
  author = {K. -K. Sung and T. Poggio},
  title = {Example-Based Learning for View-Based Human Face Detection},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1996},
  volume = {20},
  pages = {39 - 51},
  number = {1},
  month = {Jan},
  abstract = {We present an example-based learning approach for locating vertical
	frontal views of human faces in complex scenes. The technique models
	the distribution of human face patterns by means of a few view-based
	"face" and "nonface" model clusters. At each image location, a difference
	feature vector is computed between the local image pattern and the
	distribution-based model. A trained classifier determines, based
	on the difference feature vector measurements, whether or not a human
	face exists at the current image location. We show empirically that
	the distance metric we adopt for computing difference feature vectors,
	and the "nonface" clusters we include in our distribution-based model,
	are both critical for the success of our system.}
}

@ARTICLE{Swet1996,
  author = {D.L. Swet and J. Weng},
  title = {Using Discriminant Eigenfeatures for Image Retrieval},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1996},
  volume = {18},
  pages = {831-836}
}

@BOOK{Taylor2004,
  title = {Kernel Methods for Pattern Analysis},
  publisher = {Cambridge University Press},
  year = {2004},
  author = {John Shawe Taylor and Nello Cristianini},
  timestamp = {2008.01.31}
}

@ARTICLE{Tefas2001,
  author = {A. Tefas and C. Kotropoulos and I. Pitas},
  title = {Using Support Vector Machines to Enhance the Performance of Elastic
	Graph Matching for Frontal Face Authentication},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2001},
  volume = {23},
  pages = {735-746},
  number = {7},
  month = {July}
}

@ARTICLE{Tenenbaum2000,
  author = {Joshua B. Tenenbaum and Vin de Silva and John C. Langford},
  title = {A Global Geometric Framework for Nonlinear Dimensionality Reduction},
  journal = {SCIENCE},
  year = {2000},
  volume = {290},
  pages = {2319-2323}
}

@INPROCEEDINGS{Terrillon2000,
  author = {T. Terrillon and M. Shirazi and M.Sadek and H. Fukamachi and S. Akamatsu},
  title = {Invariant Face Detection with Support Vector Machines},
  booktitle = {Proceedings of the 15th International Conference on Pattern Recognition},
  year = {2000},
  volume = {4},
  pages = {210-217},
  month = {September},
  abstract = {This paper present an analysis of the performance of support vector
	machines (SVMs) for automatic detection of human faces in static
	color images of complex scenes. Skin color-based image segmentations
	initially performed for several different chrominance spaces by use
	of the single Gaussian chrominance model and a Gaussian mixture density
	model. Feature extraction in the segmented images is then implemented
	by use of invariant orthogonal Fourier-Mellin moments. For all chrominance
	spaces, the application of SVMs to the invariant moments obtained
	from a set of 100 test images yields a higher face detection performance
	than when applying a 3-layer perceptron neural network (NN), depending
	on a suitable selection of the kernel function used to train the
	SVM and of the value of its associated parameter(s). The training
	of SVMs is easier and faster than that of a NN, always finds a global
	minimum, and SVMs have a better generalization ability}
}

@ARTICLE{Teuner1995,
  author = {Andreas Teuner and Olaf Pichler and Bedrich J. Hosticka},
  title = {Unsupervised Texture Segmentation of Image Using Tuned Matched Gabor
	Filters},
  journal = {IEEE Transactions on Image Processing},
  year = {1995},
  volume = {4},
  pages = {863-870},
  number = {6}
}

@INCOLLECTION{Thain2002,
  author = {Douglas Thain and Todd Tannenbaum and Miron Livny},
  title = {{C}ondor and the {G}rid},
  booktitle = {Grid Computing: Making the Global Infrastructure a Reality},
  publisher = {John Wiley \& Sons Inc.},
  year = {2002},
  editor = {Fran Berman and Geoffrey Fox and Tony Hey},
  month = {December}
}

@ARTICLE{Turk1991,
  author = {M. Turk and A. Pentland},
  title = {Eigenfaces for Recognition},
  journal = {Journey of Cognitive Neuroscience},
  year = {1991},
  volume = {3},
  pages = {71-86},
  number = {1}
}

@ARTICLE{Valiant1984,
  author = {L. G. Valiant},
  title = {A Theory of the Learnable},
  journal = {Communications of the ACM},
  year = {1984},
  volume = {27},
  pages = {1134-1142}
}

@BOOK{Vapnik1995,
  title = {The Nature of Statistical Learning Theory},
  publisher = {Springer-Verlag},
  year = {1995},
  editor = {New York},
  author = {V. Vapnik}
}

@ARTICLE{Viola2004,
  author = {P. Viola and M. Jones},
  title = {Robust Real-time Object Detection},
  journal = {International Journal of Computer Vision},
  year = {2004},
  volume = {57},
  pages = {137-154},
  number = {2},
  month = {May},
  abstract = {This paper describes a face detection framework that is capable of
	processing images extremely rapidly while achieving high detection
	rates. There are three key contributions. The first is the introduction
	of a new image representation called the Integral Image which allows
	the features used by our detector to be computed very quickly. The
	second is a simple and efficient classifier which is built using
	the AdaBoost learning algorithm (Freund and Schapire, 1995) to select
	a small number of critical visual features from a very large set
	of potential features. The third contribution is a method for combining
	classifiers in a cascade which allows background regions of the image
	to be quickly discarded while spending more computation on promising
	face-like regions. A set of experiments in the domain of face detection
	is presented. The system yields face detection performance comparable
	to the best previous systems (Sung and Poggio, 1998; Rowley et al.,
	1998; Schneiderman and Kanade, 2000; Roth et al., 2000). Implemented
	on a conventional desktop, face detection proceeds at 15 frames per
	second.}
}

@INPROCEEDINGS{Viola2001,
  author = {P. Viola and M. Jones},
  title = {Rapid Object Detection using a Boosted Cascade of Simple Features},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition},
  year = {2001},
  volume = {1},
  pages = {511-518}
}

@ARTICLE{Wactlar1996,
  author = {H.D. Wactlar and T. Kanade and M.A. Smith and S.M. Stevens},
  title = {Intelligent Access to Digital Video: Informedia Project},
  journal = {IEEE Computing},
  year = {1996},
  volume = {29},
  pages = {46-52},
  number = {5}
}

@INPROCEEDINGS{Wang2000,
  author = {C. Wang and S.M. Griebel and M.S. Brandstein},
  title = {Robust Automatic Video-Conferencing with Multiple Cameras and Microphones},
  booktitle = {Proceedings of IEEE international Conference on Multimedia and Expo},
  year = {2000}
}

@CONFERENCE{Wang2006,
  author = {H. Wang and J. Yin and J. Pei and P. S. Yu and J. X. Yu},
  title = {Suppressing Model Overfitting in Mining Concept-Drifting Data Streams},
  booktitle = {Proceedings of the 12th ACM SIGKDD International Conference on Knowledge
	Discovery and Data Mining (KDD'06)},
  year = {2006},
  owner = {sir02mz},
  timestamp = {2008.06.06}
}

@CONFERENCE{Weyrauch2004,
  author = {B. Weyrauch and J. Huang and B. Heisele and V. Blanz},
  title = {Component-based face recognition with {3D} morphable models},
  booktitle = {Proceedings of CVPR Workshop on Face Processing in Video (FPIV'04)},
  year = {2004}
}

@MISC{wiki:LUT,
  author = {Wikipedia},
  title = {Lookup table --- Wikipedia{,} The Free Encyclopedia},
  year = {2008},
  note = {[Online; accessed 9-May-2008]},
  url = {\url{http://en.wikipedia.org/w/index.php?title=Lookup_table&oldid=208031351}}
}

@MISC{wiki:ppm,
  author = {Wikipedia},
  title = {Netpbm format --- Wikipedia{,} The Free Encyclopedia},
  year = {2008},
  note = {[Online; accessed 21-April-2008]},
  url = {http://en.wikipedia.org/w/index.php?title=Netpbm_format&oldid=201875818}
}

@INPROCEEDINGS{Wiskott1999,
  author = {L. Wiskott and J.M. Fellous and N. Kruger and C. Malsburg},
  title = {Face Recognition by Elastic Bunch Graph Matching},
  booktitle = {Intelligent Biometric Techniques in Fingerprint and Face Recognition},
  year = {1999},
  editor = {L.C. Jain et al},
  pages = {355-396},
  publisher = {CRC Press}
}

@ARTICLE{Wiskott1997,
  author = {L. Wiskott and J.M. Fellous and N. Kruger and C. Malsburg},
  title = {Face Recognition by Elastic Bunch Graph Matching},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {1997},
  volume = {19},
  pages = {775-779}
}

@CONFERENCE{Wu2004glasses,
  author = {Bo Wu and Haizhou Ai and Ran Liu},
  title = {Glasses Detection by Boosting Simple Wavelet Features},
  booktitle = {ICPR '04: Proceedings of the Pattern Recognition, 17th International
	Conference on (ICPR'04) Volume 1},
  year = {2004},
  pages = {292--295},
  organization = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  doi = {http://dx.doi.org/10.1109/ICPR.2004.416}
}

@CONFERENCE{Wu2004,
  author = {X.J. Wu and J. Kittler and J.Y. Yang and K. Messer and S.T. Wang},
  title = {A new Direct {LDA} ({D-LDA}) Algorithm for Feature Extraction in
	Face Recognition.},
  booktitle = {Proceedings of International Conference on Pattern Recognition},
  year = {2004}
}

@INPROCEEDINGS{Xu1998,
  author = {G. Xu and T. Sugimoto},
  title = {Rits eye: A Software-based System for Realtime Face Detection and
	Tracking using Pan-tilt-zoom Controllable Camera},
  booktitle = {Proceedings of International Conference on Pattern Recognition},
  year = {1998}
}

@ARTICLE{Yang2004,
  author = {J. Yang and D. Zhang and A.F. Frangi and J. Yang},
  title = {Two-dimensional {PCA}: a new approach to appearance-based face representation
	and recognition},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year = {2004},
  volume = {26},
  pages = {131-137}
}

@CONFERENCE{Yang2002,
  author = {M.H. Yang},
  title = {Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using
	Kernel Methods},
  booktitle = {Proceedings of the Fifth IEEE International Conference on Automatic
	Face and Gesture Recognition},
  year = {2002}
}

@CONFERENCE{Yang2002ICIP,
  author = {Ming-Hsuan Yang},
  title = {Face recognition using extended isomap},
  booktitle = {Proceedings of Image Processing. 2002. Proceedings. 2002 International
	Conference on},
  year = {2002}
}

@CONFERENCE{Yang2004fg,
  author = {Peng Yang and Shiguang Shan and Wen Gao and Stan Li and Dong Zhang},
  title = {Face Recognition Using {Ada-Boosted} Gabor Features},
  booktitle = {Proceedings of the 6th IEEE International Conference on Automatic
	Face and Gesture Recognition},
  year = {2004}
}

@CONFERENCE{Young2005,
  author = {David Young and James Ferryman},
  title = {Faster learning via optimised {A}daboost},
  booktitle = {IEEE Conference on Advanced Video and Signal Based Surveillance,
	2005. AVSS 2005.},
  year = {2005}
}

@ARTICLE{Yow1997,
  author = {K. Yow and R. Cipolla},
  title = {Feature-based human face detection},
  journal = {Image and Vision Computing},
  year = {1997},
  volume = {15},
  pages = {713-735},
  number = {9}
}

@INPROCEEDINGS{Zhang1998,
  author = {Z. Zhang and M. Lyons and M. Schuster and S. Akamastsu},
  title = {Comparison between Geometry-Based and Gabor Wavelets-Based Facial
	Expression Recognition Using Multi-Layer Perceptron},
  booktitle = {Proceeding of International Conference on Automatic Face and Gesture
	Recognition},
  year = {1998},
  volume = {1},
  pages = {454-457}
}

@CONFERENCE{Zhao2000,
  author = {W. Zhao and R. Chellappa},
  title = {{SFS} based view synthesis for robust face recognition},
  booktitle = {Proceedings of IEEE International Conference on Automatic Face and
	Gesture Recognition},
  year = {2000},
  pages = {285-292}
}

@INPROCEEDINGS{Zhao1998,
  author = {W. Zhao and R. Chellappa and A. Krishnaswamy},
  title = {Discriminant Analysis of Principal Components for Face Recognition},
  booktitle = {Proceedings of the 3rd IEEE International Conference on Face and
	Gesture Recognition, FG'98},
  year = {1998}
}

@ARTICLE{Zhao2003,
  author = {W. Zhao and R. Chellappa and A. Rosenfeld and P.J. Phillips},
  title = {Face Recognition: A Literature Survey},
  journal = {ACM Computing Surveys},
  year = {2003},
  volume = {1},
  pages = {399-458}
}

@CONFERENCE{zhou2006icpr,
  author = {Mian Zhou and Hong Wei},
  title = {Face Verification Using Gabor Wavelets and {A}daBoost},
  booktitle = {Proceedings of 18th International Conference on Pattern Recognition},
  year = {2006}
}

@CONFERENCE{zhou2006acv,
  author = {Mian Zhou and Hong Wei and Stephen J. Maybank},
  title = {Gabor Wavelets and {A}daBoost in Feature Selection for Face Verification},
  booktitle = {Proceedings of Applications of Computer Vision 2006 workshop in conjunction
	with ECCV2006},
  year = {2006},
  pages = {101-109},
  month = {May}
}

@CONFERENCE{Zhou2004,
  author = {S. Zhou and R. Chellappa and B. Moghaddam},
  title = {Intra-personal kernel space for face recognition},
  booktitle = {Proceedings of the 6th International Conference on Automatic Face
	and Gesture Recognition, FGR2004,},
  year = {2004}
}

@UNPUBLISHED{Zhu2006,
  author = {Ji Zhu and Saharon Rosset and Hui Zhou and Trevor Hastie},
  title = {Multi-class {A}daBoost},
  note = {A multiclass generalization of the Adaboost algorithm, based on a
	generalization of the exponential loss},
  year = {2006}
}

@MISC{biomcons,
  title = {Biometric {C}onsortium, http://www.biometrics.org},
  url = {http://www.biometrics.org/}
}

@MISC{intlbiogroup,
  title = {International Biometrics Group, http://www.biometricgroup.com}
}

